Recent reviews of the overall quality of legislative initiatives to bolster preventative care and deter costs through the adoption of the Patient-Centered Medical Home (PCMH) model have been mixed. The reasons for these findings vary, and important gaps exist in our understanding of the circumstances in which some medical homes apparently flourish while others do not. In particular, the degree to which geography and associated social determinants of health drive variations in care quality is not well understood. This understanding is critical for promoting access standards of service availability given the geographic variation in which the medical homes are reaching the marketplace. As in other states, South Carolina?s Medicaid program recently began a state-established initiative to allow enrollees to obtain care through recognized PCMHs that participated in Medicaid Managed Care (MMC). Since that time, beneficiaries have been eligible to self-enroll into 297 of the 367 medical homes that are recognized by the National Committee for Quality Assurance and that participate in MMC. Although the program is available to enrollees across the state, 10% of the total Medicaid population must travel outside of their county of residence to access a PCMH. The four counties that contain half of all medical homes account for less than 30% of the total Medicaid population. Medicaid?s enrollment structure and distribution of medical homes provides an opportunity to conduct a ?natural experiment? to analyze whether longer travel distances and times to providers determines why the effects of some PCMH innovations are often muted. Using a difference-in-difference design, this study will examine whether the longer travel distances and times to care decreases observed differences in avoidable emergency department (ED) visits and avoidable inpatient hospitalizations. We will extend this analysis to minorities as well as populations living in racially segregated neighborhoods to determine if distance effects represent a higher burden to specific patient groups. Administrative data will be derived from a combination of Medicaid claims data for recipients that were consecutively enrolled from 2016 to 2018, street network data, and American Community Survey, which will be used to build socioeconomic and neighborhood segregation indices. The study analyzes accessibility thresholds that are already incorporated into MMC primary and specialty care contracts as a mechanism from which to recommend specific standards for PCMHs. Regression analyses will explore the relationship between travel times and distances on avoidable ED and inpatient visits by comparing PCMH enrollees to Medicaid recipients who have never entered into the PCMH program, examining the association between moderators (e.g., neighborhood segregation) and mediators (e.g., primary care quality) with proximity to preventive care. Findings will have relevance to current MMC network adequacy policy reform efforts and for establishing parameters about the location of PCMHs for optimum accessibility.